Search results for "Semantic analytics"

showing 10 items of 21 documents

Semantic web technologies for facilities management

2007

Facility management is the practice of coordinating the physical workplace with the people and work of the organization. It integrates the principles of business administration, architecture and the behavioral and engineering sciences. To deal with these requirements, we have developed a framework based on Semantic Web technologies: RDF, OWL, SWRL and named graph. This framework, called C-DMF, allows facilities manager to organize all knowledge generating during building lifecycle in end-user contextual graphs.

Web standardsKnowledge managementComputer sciencebusiness.industrycomputer.internet_protocolSocial Semantic WebOWL-SWorld Wide WebSemantic gridSemantic analyticsSemantic Web StackbusinesscomputerSemantic WebData Web2007 2nd International Conference on Digital Information Management
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Context DataModel Framework: semantic facilities management

2008

Facility management is the practice of coordinating the physical workplace with the people and work of the organisation. It integrates the principles of business administration, architecture and the behavioural and engineering sciences. Software dedicated to facility management are usually limited to spreadsheet software. With the development of the Industry Foundation Class (IFC; a new object-oriented standard to model buildings) and web-based networks, a new generation of methods and tools dedicated to facility management are required. To deal with these requirements, we have developed a framework based on Semantic Web technologies: RDF, Ontology Web Language (OWL), Semantic Web Rule Lang…

Web standardsKnowledge managementbusiness.industrySemantic Web Rule Languagecomputer.internet_protocolComputer scienceManagement Science and Operations ResearchOWL-SSocial Semantic WebSemantic analyticsSemantic Web StackBusiness and International ManagementSafety Risk Reliability and QualitySoftware engineeringbusinesscomputerSemantic WebData WebInternational Journal of Product Lifecycle Management
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Ontology languages for the semantic web: A never completely updated review

2006

This paper gives a never completely account of approaches that have been used for the research community for representing knowledge. After underlining the importance of a layered approach and the use of standards, it starts with early efforts used for artificial intelligence researchers. Then recent approaches, aimed mainly at the semantic web, are described. Coding examples from the literature are presented in both sections. Finally, the semantic web ontology creation process, as we envision it, is introduced.

Web standardsOntology Inference LayerInformation Systems and ManagementKnowledge representation and reasoningComputer sciencecomputer.internet_protocolProcess ontologyOntology (information science)computer.software_genreSocial Semantic WebOWL-SManagement Information SystemsWorld Wide WebOpen Biomedical OntologiesArtificial IntelligenceSemantic computingSemantic analyticsUpper ontologySemantic Web StackSemantic Webbusiness.industryOntology-based data integrationSuggested Upper Merged OntologyOntology languageOntologyArtificial intelligencebusinessWeb intelligencecomputerOntology alignmentSoftwareNatural language processingKnowledge-Based Systems
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Ontology-based Semantic Web Service platform in Mobile Environments

2006

The number of mobile terminals is continuously increasing in the world, although in many developed countries the market has saturated. Thus, the market can only grow if new service types are offered to the mobile terminals. One emerging technology that might make this possible is semantic web services. At the core of this technology are ontologies that are necessary for automatic discovery and composition of the services. In this paper we discuss how mobility affects the architectural considerations of semantic web service platform and particularly ontology management. We rely on reference architecture for Semantic Web Services in our work.

Web standardsbusiness.industryComputer sciencecomputer.internet_protocolcomputer.software_genreSocial Semantic WebOWL-SWorld Wide WebSemantic analyticsSemantic Web StackWeb servicebusinesscomputerSemantic WebData Web7th International Conference on Mobile Data Management (MDM'06)
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Semantic Web Enabled Web Services: State-of-Art and Industrial Challenges

2003

Semantic Web technology has a vision to define and link Web data in a way that it can be understood and used by machines for automation, integration and reuse of data across various applications. Ontological definition of every resource as it is assumed in Semantic Web, along with new techniques for semantics processing and new vision Intelligent Web Services is expected to bring Web on its new level. At present, Web Services technology is stressed by the search of a right way for further development. Combination of Semantic Web and Web Services concepts may address many of difficulties of existing technology. It is not a question of whether Semantic Web is coming or not, but a question of …

Web standardsmedicine.medical_specialtyWeb 2.0Web developmentComputer scienceService discoveryWeb engineeringReusecomputer.software_genreSocial Semantic WebWorld Wide WebWeb designSemantic analyticsmedicineWeb navigationSemantic Web StackRDFSemantic WebData Webbusiness.industrycomputer.file_formatWeb application securityOntologyThe InternetWeb mappingWeb servicebusinessWeb intelligenceWS-PolicycomputerWeb modelingInformation integration
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Ontosmartresource: an industrial resource generation in semantic web

2005

Semantic Web is a logical evolution of the existing Web. It was meant to serve for machines as today's Web does for humans. The term "machines" according to the existing semantic Web's vocabulary mostly means "computers". However industry needs such applications, which consider machines also as embedded computational entities within field devices, personal devices, microwave ovens, etc. In other words, now we should involve the real (industrial) world objects as resources into semantic Web. Still the main object of such a world will be a human, which becoming a resource (not just a user of resources) in the distributed environment. In this paper we introduce an extension of the semantic Web…

Web standardsmedicine.medical_specialtybusiness.industryComputer scienceSocial Semantic WebWorld Wide WebSemantic gridmedicineSemantic analyticsSemantic Web StackbusinessSemantic WebWeb modelingData Web2nd IEEE International Conference on Industrial Informatics, 2004. INDIN '04. 2004
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Interpreting Heterogeneous Geospatial Data Using Semantic Web Technologies

2016

International audience; The paper presents work on implementation of semantic technologies within a geospatial environment to provide a common base for further semantic interpretation. The work adds on the current works in similar areas where priorities are more on spatial data integration. We assert that having a common unified semantic view on heterogeneous datasets provides a dimension that allows us to extend beyond conventional concepts of searchability, reusability, composability and interoperability of digital geospatial data. It provides contextual understanding on geodata that will enhance effective interpretations through possible reasoning capabilities. We highlight this through …

[ INFO ] Computer Science [cs]Geospatial analysisComputer scienceInteroperabilitySemantification02 engineering and technologySDIcomputer.software_genreSocial Semantic Web020204 information systems0202 electrical engineering electronic engineering information engineeringSemantic analyticsGeospatial PDF[INFO]Computer Science [cs]Web Coverage ServiceSemantic Web StackSemantic WebData WebR2RMLInformation retrievalLand usebusiness.industryCIPcomputer.file_formatGeoSPARQLInteroperabilityGeoSPARQLSemantic technology020201 artificial intelligence & image processingHeterogeneitybusinesscomputer
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Qualifying semantic graphs using model checking

2011

International audience; Semantic interoperability problems have found their solutions using languages and techniques from the Semantic Web. The proliferation of ontologies and meta-information has improved the understanding of information and the relevance of search engine responses. However, the construction of semantic graphs is a source of numerous errors of interpretation or modeling and scalability remains a major problem. The processing of large semantic graphs is a limit to the use of semantics in current information systems. The work presented in this paper is part of a new research at the border of two areas: the semantic web and the model checking. This line of research concerns t…

[ INFO.INFO-MO ] Computer Science [cs]/Modeling and Simulation[INFO.INFO-WB] Computer Science [cs]/WebComputer science[ INFO.INFO-WB ] Computer Science [cs]/Web0102 computer and information sciences02 engineering and technologycomputer.software_genre01 natural sciencesSocial Semantic Webtemporal logicSemantic similaritySemantic computing0202 electrical engineering electronic engineering information engineeringSemantic analyticsSemantic integrationSemantic Web StackInformation retrievalbusiness.industry[INFO.INFO-WB]Computer Science [cs]/WebSemantic search020207 software engineeringSemantic interoperability[INFO.INFO-MO]Computer Science [cs]/Modeling and SimulationModel-checking010201 computation theory & mathematicsSemantic graphTheoryofComputation_LOGICSANDMEANINGSOFPROGRAMS[INFO.INFO-MO] Computer Science [cs]/Modeling and SimulationArtificial intelligencebusinesscomputerNatural language processing2011 International Conference on Innovations in Information Technology
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Temporal Logic To Query Semantic Graphs Using The Model Checking Method

2012

International audience; Semantic interoperability problems have found their solutions due to the use of languages and techniques from the Semantic Web. The proliferations of ontologies and meta-information have improved the understanding of information and the relevance of search engine responses. However, the construction of semantic graphs is a source of numerous errors of interpretation or modeling, and scalability remains a major problem. The processing of large semantic graphs is a limit to the use of semantics in current information systems. The work presented in this paper is part of a new research at the border of two areas: the semantic web and the model checking. This line of rese…

[INFO.INFO-WB] Computer Science [cs]/WebComputer science[INFO.INFO-SE] Computer Science [cs]/Software Engineering [cs.SE][ INFO.INFO-WB ] Computer Science [cs]/WebSPARQL.02 engineering and technology[INFO.INFO-SE]Computer Science [cs]/Software Engineering [cs.SE][ INFO.INFO-SE ] Computer Science [cs]/Software Engineering [cs.SE]Ontology (information science)computer.software_genreQuery languagetemporal logic querySPARQLSocial Semantic WebSearch engineDescription logicSemantic similaritytemporal logicArtificial IntelligenceWeb query classificationSemantic computing0202 electrical engineering electronic engineering information engineeringInformation systemSemantic analyticsSPARQLSemantic Web StackRDFSemantic Webcomputer.programming_language[INFO.INFO-SC]Computer Science [cs]/Symbolic Computation [cs.SC]Web search querySemantic Web Rule LanguageProgramming languagebusiness.industry[INFO.INFO-SC] Computer Science [cs]/Symbolic Computation [cs.SC][INFO.INFO-WB]Computer Science [cs]/Web020207 software engineeringcomputer.file_formatSemantic interoperabilitymodel checking[ INFO.INFO-SC ] Computer Science [cs]/Symbolic Computation [cs.SC]Human-Computer InteractionSemantic graph020201 artificial intelligence & image processingbusinesscomputerSoftwareRDF query language
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General Adaption Framework

2005

Integration of heterogeneous applications and data sources into an interoperable system is one of the most relevant challenges for many knowledge-based corporations nowadays. Development of a global environment that would support knowledge transfer from human experts to automated Web services, which are able to learn, is a very profit-promising and challenging task. The domain of industrial maintenance is not an exception. This paper outlines in detail an approach for adaptation of heterogeneous Web resources into a unified environment as a first step toward interoperability of smart industrial resources, where distributed human experts and learning Web services are utilized by various devi…

medicine.medical_specialtyComputer Networks and CommunicationsComputer sciencebusiness.industrySemantic interoperabilitySocial Semantic WebWorld Wide WebSemantic gridSemantic analyticsmedicineSemantic Web StackbusinessSemantic WebWeb modelingData WebInformation SystemsInternational Journal on Semantic Web and Information Systems
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